An examination of automatic video retrieval technology on access to the contents of an historical video archive

Purpose – This paper aims to provide an initial understanding of the constraints that historical video collections pose to video retrieval technology and the potential that online access offers to both archive and users. Design/methodology/approach – A small and unique collection of videos on customs and folklore was used as a case study. Multiple methods were employed to investigate the effectiveness of technology and the modality of user access. Automatic keyframe extraction was tested on the visual content while the audio stream was used for automatic classification of speech and music clips. The user access (search vs browse) was assessed in a controlled user evaluation. A focus group and a survey provided insight on the actual use of the analogue archive. The results of these multiple studies were then compared and integrated (triangulation). Findings – The amateur material challenged automatic techniques for video and audio indexing, thus suggesting that the technology must be tested against the material before deciding on a digitisation strategy. Two user interaction modalities, browsing vs searching, were tested in a user evaluation. Results show users preferred searching, but browsing becomes essential when the search engine fails in matching query and indexed words. Browsing was also valued for serendipitous discovery; however the organisation of the archive was judged cryptic and therefore of limited use. This indicates that the categorisation of an online archive should be thought of in terms of users who might not understand the current classification. The focus group and the survey showed clearly the advantage of online access even when the quality of the video surrogate is poor. The evidence gathered suggests that the creation of a digital version of a video archive requires a rethinking of the collection in terms of the new medium: a new archive should be specially designed to exploit the potential that the digital medium offers. Similarly, users' needs have to be considered before designing the digital library interface, as needs are likely to be different from those imagined. Originality/value – This paper is the first attempt to understand the advantages offered and limitations held by video retrieval technology for small video archives like those often found in special collections

Exploiting tacit knowledge through knowledge management technologies

The purpose of this paper is to examine the contributions and suitability of the available knowledge management (KM) technologies, including the Web 2.0 for exploiting tacit knowledge. It proposes an integrated framework for extracting tacit knowledge in organisations, which includes Web 2.0 technologies, KM tools, organisational learning (OL) and Community of Practice (CoP). It reviews a comprehensive literature covering overview of KM theories, KM technologies and OL and identifies the current state of knowledge relating to tacit knowledge exploitation. The outcomes of the paper indicate that Internet and Web 2.0 technologies have stunning prospects for creating learning communities where tacit knowledge can be extracted from people. The author recommends that organisations should design procedures and embed them in their Web 2.0 collaborative platforms persuading employees to record their ideas and share them with other members. It is also recommended that no idea should be taken for granted in a learning community where tacit knowledge exploitation is pursued. It is envisaged that future research should adopt empirical approach involving Complex Adaptive Model for Tacit Knowledge Exploitation (CAMTaKE) and the Theory of Deferred Action in examining the effectiveness of KM technologies including Web 2.0 tools for tacit knowledge exploitation

Applying semantic web technologies to knowledge sharing in aerospace engineering

This paper details an integrated methodology to optimise Knowledge reuse and sharing, illustrated with a use case in the aeronautics domain. It uses Ontologies as a central modelling strategy for the Capture of Knowledge from legacy docu-ments via automated means, or directly in systems interfacing with Knowledge workers, via user-defined, web-based forms. The domain ontologies used for Knowledge Capture also guide the retrieval of the Knowledge extracted from the data using a Semantic Search System that provides support for multiple modalities during search. This approach has been applied and evaluated successfully within the aerospace domain, and is currently being extended for use in other domains on an increasingly large scale

ISDN at NASA Lewis Research Center

An expository investigation of the potential impact of the Integrated Services Digital Network (ISDN) at NASA Lewis Research Center is described. To properly frame the subject, the paper contains a detailed survey of the components of Narrowband ISDN. The principles and objectives are presented as decreed by the Consultative Committee for International Telephone and Telegraph (CCITT). The various channel types are delineated and their associated service combinations are described. The subscriber-access network functions are explained pictorially via the ISDN reference configuration. A section on switching techniques is presented to enable the reader to understand the emergence of the concept of fast packet switching. This new technology is designed to operate over the high bandwidth, low error rate transmission media that characterizes the LeRC environment. A brief introduction to the next generation of networks is covered with sections on Broadband ISDM (B-ISDN), Asynchronous Transfer Mode (ATM), and Synchronous Optical Networks (SONET). Applications at LeRC are presented, first in terms of targets of opportunity, then in light of compatibility constraints. In-place pilot projects and testing are described that demonstrate actual usage at LeRC

Image Search with Text Feedback by Visiolinguistic Attention Learning

Image search with text feedback has promising impacts in various real-world applications, such as e-commerce and internet search. Given a reference image and text feedback from user, the goal is to retrieve images that not only resemble the input image, but also change certain aspects in accordance with the given text. This is a challenging task as it requires the synergistic understanding of both image and text. In this work, we tackle this task by a novel Visiolinguistic Attention Learning (VAL) framework. Specifically, we propose a composite transformer that can be seamlessly plugged in a CNN to selectively preserve and transform the visual features conditioned on language semantics. By inserting multiple composite transformers at varying depths, VAL is incentive to encapsulate the multi-granular visiolinguistic information, thus yielding an expressive representation for effective image search. We conduct comprehensive evaluation on three datasets: Fashion200k, Shoes and FashionIQ. Extensive experiments show our model exceeds existing approaches on all datasets, demonstrating consistent superiority in coping with various text feedbacks, including attribute-like and natural language descriptions

Optimizing University Mobility : An Internal Navigation and Crowd Management System

In the evolving landscape of educational technology, the article explores the critical frontier of indoor navigation systems, focusing on universities. Traditional approaches in higher education often fall short of meeting dynamic user expectations, necessitating revolutionary solutions. This research introduces an innovative internal navigation and crowd management system that seamlessly integrates augmented reality, natural language processing, machine learning, and image processing technologies. The Android platform serves as the foundation, harnessing augmented reality's transformative capabilities to provide real-time visual cues and personalized wayfinding experiences. The voice interaction module, backed by NLP and ML, creates an intelligent, context-aware assistant. The crowd management module, employing advanced image processing, delivers real-time crowd density insights. Personalized recommendations, powered by NLP and ML, offer tailored canteen suggestions based on user preferences. The agmented reality navigation module, using Mapbox, Unity Hub, AR Core, and Vuforia, enriches the user experience with dynamic visual cues. Results reveal the success of each module: the voice interaction module showcases continuous learning, user-centric feedback, contextual guidance excellence, robust security, and multimodal interaction flexibility. The crowd management module excels in video feed processing, image processing with OpenCV, and real-time availability information retrieval. The personalized recommendations module demonstrates high accuracy, equilibrium, and robust performance. The AR navigation module impresses with precision, enriched navigation, and tailored routes through machine learning. This cohesive system sets new benchmarks for user-centric technology in universities. Future work includes multi-university integration, intelligent spatial design, and real-time decision support, paving the way for more efficient, user-centered university experiences and contributing to the advancement of smart university environments. The research serves as a pivotal force in reshaping interactions within university spaces, envisioning a future where technology seamlessly enhances the essence of human interaction in educational environments

Mixing Modalities of 3D Sketching and Speech for Interactive Model Retrieval in Virtual Reality

Sketch and speech are intuitive interaction methods that convey complementary information and have been independently used for 3D model retrieval in virtual environments. While sketch has been shown to be an effective retrieval method, not all collections are easily navigable using this modality alone. We design a new challenging database for sketch comprised of 3D chairs where each of the components (arms, legs, seat, back) are independently colored. To overcome this, we implement a multimodal interface for querying 3D model databases within a virtual environment. We base the sketch on the state-of-the-art for 3D Sketch Retrieval, and use a Wizard-of-Oz style experiment to process the voice input. In this way, we avoid the complexities of natural language processing which frequently requires fine-tuning to be robust. We conduct two user studies and show that hybrid search strategies emerge from the combination of interactions, fostering the advantages provided by both modalities

Technology Target Studies: Technology Solutions to Make Patient Care Safer and More Efficient

Presents findings on technologies that could enhance care delivery, including patient records and medication processes; features and functionality nurses require, including tracking, interoperability, and hand-held capability; and best practices

Simulation verification techniques study

Results are summarized of the simulation verification techniques study which consisted of two tasks: to develop techniques for simulator hardware checkout and to develop techniques for simulation performance verification (validation). The hardware verification task involved definition of simulation hardware (hardware units and integrated simulator configurations), survey of current hardware self-test techniques, and definition of hardware and software techniques for checkout of simulator subsystems. The performance verification task included definition of simulation performance parameters (and critical performance parameters), definition of methods for establishing standards of performance (sources of reference data or validation), and definition of methods for validating performance. Both major tasks included definition of verification software and assessment of verification data base impact. An annotated bibliography of all documents generated during this study is provided